Method and apparatus for aggregating and presenting data associated with geographic locations

ABSTRACT

Implementations relate to systems and methods for aggregating and presenting data related to geographic locations. Geotag data related to geographic locations and associated features or attributes can be collected to build a regional profile characterizing a set of locations within the region. Geotag data related to the constituent locations, such as user ratings or popularity ranks for restaurants, shops, parks, or other features, sites, or attractions, can be combined to generate a profile of characteristics of locations in the region. The platform can generate recommendations of locations to transmit to the user of a mobile device, based for instance on the location of the device in the region as reported by GPS or other location service and the regional profile. Geotag data can include audio data analyzed using region-specific terms, and user recommendations can be presented via dynamic menus based on regional profiles, user preferences or other criteria.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation of U.S. application Ser. No.15/385,539, filed Dec. 20, 2016, entitled “Method and Apparatus forAggregating and Presenting Data Associated with Geographic Locations,”which is a continuation of U.S. application Ser. No. 12/470,475, filedMay 21, 2009, entitled “Method and Apparatus for Aggregating andPresenting Data Associated with Geographic Locations,” which claimspriority to U.S. Provisional Application No. 61/056,406, filed May 27,2008, entitled “Method and Apparatus for Aggregating and Presenting DataAssociated with Geographic Locations,” assigned or under obligation ofassignment to the same entity as this application, and which provisionalapplication is incorporated by reference herein.

BACKGROUND

The present teachings relate generally to aggregation and presentationof data associated with geographic locations, and more particularly, tothe analysis of geographic data tags generated by mobile devices orother sources to generate a regional profile characterizing features,attractions, and other points of interest for a given geographic area,which can be used to generate recommendations and other services forusers.

In location-based services in cellular and other applications, a “tag”can be a keyword, text, or other attribute that is assigned to a pieceof information to describe that information. One or more tags can beassigned to a piece of information by one or more users. A geographicdata tag (“geotag”) can be a type of tag that incorporates a geographiclocation, such as latitude/longitude coordinates, along with associatedattributes. A geotag can allow descriptive information to be associatedwith a physical location on Earth.

Presently, various Websites provide a capability to add geographiclocation information to items such as digital photos, tickets, blogs,and the like. Some digital cameras have the capability to add geographiclocation information to photos when taken, but do not provide thecapability to automatically associate a piece of geotag information withthe geographic location. Moreover, while mobile phones or digitalcameras may be able to create geotags to attach to individualphotographs or other objects, and share those geotagged objects directlywith other users, no platform exists which can aggregate and analyzehigher-order attributes reflected in geotagged data received from anumber of users.

For instance, certain cellular phones may permit a user to store a mapof visited locations in a given city and input geotagged ratings ofindividual restaurants they have frequented. However, no mechanism isavailable to upload that geotag information to a collective databasethat could then, for example, assemble and sort that information to makecollective regional ratings of available restaurants to recommend to theuser population, at large. Marketing and recommendation opportunitiesmay therefore go unexploited, since the collective responses of users tovarious features and attractions in a given region are not organized ormade available to other users in the vicinity. Even local residents in aregion may not be aware of all the features and attractions available intheir region, which information could be leveraged to create interest innew travel, vacation, recreational or other possibilities for those andother users.

Techniques and platforms may therefore be desirable that provide thecapability to associate pieces of information with geographic locationsin the form of geographic data tags, and aggregate and analyze the datacontained in the geographic data tags to generate higher-level profilesof geographic regions, as well as produce associated recommendationsderived from those regional profiles.

SUMMARY

The following presents a simplified summary of one or more aspects inorder to provide a basic understanding of such aspects. This summary isnot an extensive overview of all contemplated aspects, and is intendedto neither identify key or critical elements of all aspects nordelineate the scope of any or all aspects. Its sole purpose is topresent some concepts of one or more aspects in a simplified form as aprelude to the more detailed description that is presented later.

According to the present teachings in one or more aspects, systems andmethods for aggregating and presenting data associated with geographiclocations are provided, in which a regional profiling platform operatesto receive a set of geotag data associated with geographic locations,and analyze that content to generate collective profiles of thesurrounding regions. In one or more implementations of the presentteachings, the regional profiling platform can receive multiple sets ofgeotag data, each associated with one or more geographic locations. Inone or more implementations, each of the geotags can contain ageographic identifier that identifies the associated geographiclocation. In one or more implementations, the embedded geographicidentifier can be automatically acquired simultaneously with receivingthe geotag data, and any other encoded information.

According to one or more aspects, the regional profiling platform canidentify, aggregate, organize, and store one or more attributes of theassociated geographic locations based on the collective set of geotagdata. The collective set of geotag data can be used to derive a regionalprofile for a block, tract, zip code area, city, state, country, orother geographic region.

The regional profile can include, for instance, a set of points ofinterest (POI) available in that area, such as local restaurants, parks,sporting venues, residential sections, commercial or retail centers, orother resources in the region. The regional profile in one regard canencode and summarize characteristic or prominent features, attractions,services, or other resources available in the subject region. In one ormore aspects in further regards, the regional profiling platform canaccess the regional profile developed for a given location, and use thatprofile to develop higher-order data to serve to individual users inthat area, or otherwise.

For instance, the regional profiling platform can extract features inthe set of local points of interest, and generate recommendations orsuggestions to users for restaurants, lodging, recreation,entertainment, or other features or resources available in that region,or subsection of that region. In one or more implementations, users canstore a set of individual preferences that can be used to filter therecommendations or other information they wish to receive. In one ormore aspects, user profiling data produced by platforms that track orgenerate user profiles or preferences can likewise be used to filterrecommendation information. In one or more aspects, the preferences orbehavior of the user's friends, such as members of a social networkingservice, can also be used to filter recommendation information. In oneor more aspects, users can freely add additional geotag data forlocations in a region including ratings, keywords, comments, and otherannotations associated with an area, to populate and update the databaseused to generate the regional profile. In one or more aspects, theuser-supplied geotag data can include voice clips or samples whosecontent can be decoded using customized training sets particular to agiven region. In one or more aspects, recommendation information can bepresented to the user in a dynamically ordered menu or other dialog orinterface that is adapted to the user's preferences, current location,or based on other variables.

To the accomplishment of the foregoing and related ends, the one or moreaspects comprise the features hereinafter fully described andparticularly pointed out in the claims. The following description andthe annexed drawings set forth in detail certain illustrative featuresof the one or more aspects. These features are indicative, however, ofbut a few of the various ways in which the principles of various aspectsmay be employed, and this description is intended to include all suchaspects and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate aspects of the present teachingsand together with the description, serve to explain principles of thepresent teachings. In the figures:

FIG. 1 shows an exemplary exchange of geotag-related information betweena mobile device and profiling server, according to one or more aspectsof the present teachings;

FIG. 2 illustrates an exemplary exchange of geotag-related informationbetween a mobile device and profiling server, in context with the mobiledevice in a profiled region, according to one aspect;

FIG. 3 illustrates an illustrative profiled region including a set ofpoints of interest derived from user-report sets of geotag data, alongwith the selection of an exemplary set of recommended locations in theprofiled region, according to one or more aspects;

FIG. 4 illustrates an exemplary user dialog that can be used to enteruser-supplied geotag and other data, according to one or more aspects;

FIG. 5 shows an illustrative flow diagram for generating a regionalprofile, according to one or more aspects;

FIG. 6 shows an illustrative flow diagram for generating a similarityrating or recommendation for one region compared to another, accordingto one or more aspects;

FIG. 7 shows an illustrative flow diagram for generating a similarityrating or recommendation for one location or place compared to a currentlocation, according to one or more aspects;

FIG. 8 shows an illustrative flow diagram for generating arecommendation of a destination or where to go for a user, according toone or more aspects;

FIG. 9 shows an illustrative diagram for generating a user profile fromvarious user attributes, according to one or more aspects;

FIG. 10 shows an illustrative flow diagram for generating arecommendation for a new place or location to a user, according to oneor more aspects;

FIG. 11 shows an illustrative flow diagram for generating arecommendation of a set of new user profiles most likely to visit anidentified new place, according to one or more aspects;

FIG. 12 shows an illustrative flow diagram for voice analysis of geotagdata in various regards, according to one or more aspects;

FIG. 13 shows an illustrative flow diagram for constructing a customizedtraining set for voice recognition related to geotag data, according toone or more aspects;

FIGS. 14A and 14B show illustrative recommendation views includingdynamically reordered menu elements for users in the same location and auser traveling to different locations, respectively, according to one ormore aspects;

FIG. 15 illustrates an exemplary set of hardware and other resources ina mobile device, according to implementations of the present teachings;and

FIG. 16 illustrates an exemplary set of hardware, software, and otherresources in a profiling server and associated components, according toimplementations of the present teachings.

DETAILED DESCRIPTION

Various aspects are now described with reference to the drawings. In thefollowing description, for purposes of explanation, numerous specificdetails are set forth in order to provide a thorough understanding ofone or more aspects. It may be evident; however, that such aspect(s) maybe practiced without these specific details.

In the subject description, the word “exemplary” is used to mean servingas an example, instance, or illustration. Any aspect or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Rather, use of the wordexemplary is intended to present concepts in a concrete fashion.

Moreover, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom the context, the phrase “X employs A or B” is intended to mean anyof the natural inclusive permutations. That is, the phrase “X employs Aor B” is satisfied by any of the following instances: X employs A; Xemploys B; or X employs both A and B. In addition, the articles “a” and“an” as used in this application and the appended claims shouldgenerally be construed to mean “one or more” unless specified otherwiseor clear from the context to be directed to a singular form.

Additionally, various aspects or features will be presented in terms ofsystems that may include a number of devices, components, modules, andthe like. It is to be understood and appreciated that the varioussystems may include additional devices, components, modules, etc. and/ormay not include all of the devices, components, modules etc. discussedin connection with the figures. A combination of these approaches mayalso be used.

Aspects of the present teachings relate to methods and apparatus foraggregating and presenting data associated with geographic locations.More particularly, in one or more aspects, platforms and techniques areprovided in which geographic data tags, or geotags, for specific sitesor locations are generated by mobile devices or other sources, andaggregated and analyzed to develop a regional profile for a region thatis associated with the locations. In one or more aspects, the set ofgeotag data can include user ratings, category tags, remarks, links,and/or other data, attributes, or metadata that is stored and associatedwith specific locations. For instance, retail shops located on HollywoodBoulevard in Los Angeles, Calif., can be rated or described by mobileusers or other consumers, and the ratings or other descriptive contentor tags can be associated with a geographical position (for example,captured via a Global Positioning System, or GPS fix) for thoselocations.

According to one or more aspects, a profile module hosted in a profilingserver or other resource or service can collect and combine the set ofgeotag data for a particular region, to generate the regional profilebased on geotag data for the sites or locations within the region. Theprofile module can, for instance, organize and examine the set of geotagdata and identify locations that represent or contain similar features,attractions, or resources. Thus for instance, a profiled region maycontain a number of restaurants, hotels, bed and breakfast sites, orother locations associated with travel or hospitality industries. Theprofile module can identify sets of geotag data that identify a locationas being for instance a restaurant, and further sort or organizelocations identified as restaurants into different types, such asMexican, Italian, Thai, or other categories or types. Other attributesor features of locations within a region can be identified, organized,and sorted to generate a regional profile characterizing the availablefeatures, attractions, locations, and other resources within the region.

In one or more implementations, the profiling server can receivemultiple sets of geotag data from an entire population of users, andaggregate the geotag inputs from those diverse sources into an aggregateregional profile. The regional profile can be stored in a databaseassociated with the profiling server, regional profile database, orother computing or data resources of the network. Based on theaccumulated geotag information, the profiling server can extract,identify, and sort various higher-level attributes of the geographiclocations in the region based on the geotags associated with specificgeographic positions. For example, the profiling server can determinethat an identified geographic location corresponds to an Italianrestaurant. The profiling server can search the regional profiledatabase and compile all ratings provided by users visiting andcommenting upon that location, and determine that establishment serveshighly rated pizza based on the attributes stored in the geotagsassociated with the subject geographic location. Implementations of thepresent teachings involve the profiling server aggregating the sets ofgeotag data based on the attributes of the geographic locations, andgenerating higher-level data sets from the aggregate information derivedfrom the geotags. Those outputs and services can include data, outputs,or objects such as the region profile itself, a list of similar regions,a list of similar locations, a list of users having interests keyed to alocation or region, and a list of hot spots and popular locations.

The regional profile and other data can then be used to producerecommendation information or other data related to points of interestin the region, and transmit that information to users of a mobiledevice, or other clients. For instance, the profile module can receive arequest for a recommendation, or a search query, from the user of amobile telephone or other device within, approaching, or outside aprofiled region, and extract a set of recommended destination locationswithin the region for that user. The recommendation information caninclude locations filtered based on a user profile for the user of themobile device, on a location history for that user, on a popularityrating for the potential destinations, or other criteria as well as theregional profile itself. For example, recommendation information can begenerated to suggest additional or new locations that may be similar toa location at which the mobile user is currently located. In one or moreaspects, the set of geotag data uploaded to the regional profiledatabase and/or transmitted to individual mobile devices can includeaudio data, which can be processed according to speech recognitiontraining sets derived from collected user voice inputs or otherattributes for the region. In one or more aspects, a set of categoryselections from which a user can choose recommendation information canbe generated and dynamically ordered based on user profiles orpreferences. Other delivery techniques to transmit recommendations,ratings, links, or other data related to the regional profile of aregion of interest can be used.

As used in this patent application, the term “location,” “place,” or“site” can refer to a point of interest (POI) identified or defined by alatitude/longitude reading, or other numerical or other geographicidentifier, such as a street address. As used herein, the term “region”or “geographic region” can refer to a contained area containing one ormore locations, and can mean any geographic boundary or area of varioussizes, including a single address, building, or structure, a block, atract, a county, a city, or other geographic area or unit. In one ormore aspects, a “region” can be contiguous, or can be made up of areasthat are discrete or not necessarily contiguous. In one or more aspects,a “region” can be defined by a bounded geometric shape, such as acircle, square, or polygon overlaying a map. In one or more aspects, a“region” can be defined by numerical boundaries, such as latitude andlongitude. In one or more implementations, a “region” can be defined byother identifiers, such as a ZIP code.

Likewise, in general, as used herein a “geotag” can refer to a set ofinformation associated with a defined geographic location. Theassociated information in a “geotag” can for instance be or include akeyword, tag, comment, text, video clips, images, audio samples, orother data. As used herein, the term “hotspot” can refer to a place thathas been automatically determined within a profiled region or communityto be popular, using auto-tagging or other processing. As used herein,the term “favorite place” can refer to a hotspot or other preferredlocation that is specific to a user (for instance, a home, office, orrecreation site), or determined by frequency of visitation by acommunity of users. As used herein, the term “friend” can refer to aperson identified or enumerated as a friend by a user, which can be donevia a social networking site or service.

In terms of regional profiling and related activity, as generallyillustrated in FIG. 1, a mobile device 102 operating in a wirelessnetwork hosted or supported by a base station 106 and associated networkresources can approach, travel to or within a profiled region. In one ormore aspects, mobile device 102 can include a cellular telephone, anetwork-enabled media player, a network-enabled personal digitalassistant (PDA), a WiFi′-enabled communications device, a GlobalPositioning System (GPS) unit, or other wireless, mobile, or portabledevice, client, or hardware. In one or more aspects, mobile device 102can incorporate a location module 106 to identify or capture thegeographic location or position of mobile device 102. In one or moreaspects, location module 106 can be or include variouslocation-detection technology or services, such as Global PositioningSystem (GPS), base-station triangulation, and/or trilateration, theGalileo (Global System Mobile) locator service, or other techniques tocapture or detect a location of the mobile device 102.

While registered to base station 106, mobile device 102 can generate aset of device location data 146 via location module 106, and transmit orupload device location data 146 to base station 106 via a wirelessinterface, such as a cellular interface. Base station 106 can in turncommunicate with a profiling server 170, such as a remotely hostedserver or set of servers, along with associated resources. In one ormore aspects, profiling server 170 can host a profile module 136configured to receive device location data 146 for one or more mobiledevices 102 registered to base station 106 and/or associated regionalprofiling services. Profile module 136 can in one or more aspectsidentify a profiled region in which mobile device 102 is traveling,toward which mobile device 102 is approaching, or which lies outside thevicinity of mobile device 102. Profile module 136 can subsequentlyaccess a regional profile database 116 to locate a regional profile 190for the region of interest, a user profile 118 for the user of mobiledevice 102, and generate a set of recommendation information 144 totransmit to the mobile device 102, as described herein. In one or moreaspects, the user profile 118 for the user of mobile device 102 can beentered or configured by the user him or herself, including to specifycategories or locations of interest, and/or can be generated or modifiedby profile module 136 by analysis of the user's location history, ratinghistory, transaction history, or other behavior related to profiledregion 110.

Recommendation information 144 can be presented to the user in arecommendation selector 148 displayed via a user interface 104 of mobiledevice, such as a graphical user interface. In one or moreimplementations, profile module 136 can be or include a recommendationengine such as the Xiam® recommendation engine available from XiamTechnologies Limited, a subsidiary of Qualcomm Incorporated of SanDiego, Calif. In one or more implementations, other recommendationengines or logic can also or instead be used to generate or modifyrecommendation information 144.

More particularly, and as for instance illustrated in FIG. 2, a profiledregion 110 can contain or have associated with the region a set ofpoints of interest 112, which can include, merely illustratively,locations or attractions such as Hollywood Boulevard 270, Redondo Beach272, Rodeo Drive 274, which might be registered to regional profiledatabase 116 in the case of a profiled region 110 representing orassociated with Los Angeles, Calif. Each location, place, or siteidentified in the set of points of interest 112 can have associated withit a set of geotag data 114, which can for instance be stored inregional profile database 116 or other data stores. When mobile device102 is located within profiled region 110, approaching profiled region110, the user has requested information related to profiled region 110,or at other times, profile module 136 can generate set of recommendationinformation 144 to transmit to mobile device 102 to display to the uservia user interface 104, such as a graphical user interface.

In one or more aspects, recommendation information 144 can be developedand filtered for a specific user of mobile device 102 using the user'sown user profile 118, popularity, category tag, and other informationcontained in or related to regional profile 190 hosted in regionalprofile database 116. In one or more aspects, as shown, recommendationinformation 144 can be or include a set of selectable or linkablesuggestions, identifications, or recommendations for a location to visitwithin profiled region 110. In one or more aspects, as shown,recommendation information 144 can be again presented via arecommendation selector 148 displayed on user interface 104, or othergadget, menu, dialog, or interface. In one or more aspects, the displayof recommendation information 144 via recommendation selector 148 caninclude a dialog to permit the user of mobile device 102 to view furtherinformation regarding a recommended location, such as previous userratings for that site or facility. Other attributes or informationrelated to recommendation information 144 can be presented or madeavailable to the user in recommendation selector 148, or otherinterface. In one or more aspects, tags located within the set of geotagdata 114 for one or more locations in profiled region 110 or otherwisecan be made directly linkable with each other, so that, for example, theuser of mobile device 102 can traverse all tags containing the tag“Italian restaurant,” regardless of location.

In terms of the generation, organization, and nature of regional profile190, and as for instance illustrated in FIG. 3, in one or more aspects,the collective characterization of a set of points of interest 112 in aprofiled region 110 can be aggregated into a regional profile 190reflecting the overall features of profiled region 110. The regionalprofile database 116 can, in general, profile or categorize a profiledregion 110 on an aggregate level based on the total ensemble of sets ofgeotag data 114 collected for locations in the region. The regionalprofile 190 can include one or more classifications or categorizationsof profiled region 110 based on the collective tags, ratings, comments,and/or other attributes for all sets of geotag data 114 associated withthe profiled region 110.

The boundary or area of profiled region 110 itself can be defined oridentified based on a region parameter, which can for instance include aregion identifier and/or a region size. For example, the regionparameter can include a radius and a longitude/latitude coordinateacquired by the mobile device 102, and/or calculated based on userinput. Profiled region 110 can also be defined by a predefined regionidentifier or geographic code, such as a ZIP code, a municipality name,a city name, and the like. The profile module 136 can determine oridentify a set of geographic locations located in profiled region 110,and retrieve one or more set of geotag data 114 associated with each ofthe geographic places or locations in the region. In one or moreaspects, the profile module 136 can classify the geographic locations inthe profiled region 110 region into groups of one or more similarlocations, based on the attributes of the geographic locations stored inthe set of geotag data 114 associated with the geographic locations.Profile module 136 can accordingly classify a profiled region 110 orsubsections thereof into one or more different classes, such as schoolzones, residential, commercial, parkland or recreational, and others.

Thus profile module 136 or other logic can collect, identify, sort,organize, and categorize a set of points of interest 112 for a profiledregion 110 to produce a collective or high-level characterization of theprofiled region 110 to use to deliver recommendation, search, and otherinformation to users of one or more mobile device 102, or other users.Generally speaking, the set of points of interest 112 for a givenprofiled region 110 can include any one or more of a variety of types,classes, or categories of features, locations, sites, attractions, orother resources located in profiled region 110. Those can include, asshown and merely illustratively, a first concert site 256 with anassociated set of geotag data 114, a first school 252 (illustrativelylabeled as “school 1”) with associated set of geotag data 114, a firstrestaurant 254 (illustratively labeled as “restaurant 1”) withassociated set of geotag data 114, a first sports arena 258(illustratively labeled as “sports arena 1”) with associated set ofgeotag data 114, a first office site 260 (illustratively labeled as“office site 1”) with associated set of geotag data 114, a second school262 (illustratively labeled as “school 2”) with associated set of geotagdata 114, a first residential location 266 (illustratively labeled as“residential location 1”) with associated set of geotag data 114, asecond residential location 264 (illustratively labeled as “residentiallocation 2”) with associated set of geotag data 114, and the like. Inone or more aspects, set of points of interest 112 can further include,again merely illustratively, natural and man-made features such as alake 268 or other body of water, a highway 250 (illustratively labeledas “Highway 1”), or other features, locations, sites, attractions, orother resources.

According to one or more aspects, profile module 136 or other logic cancompare the set of geotag data 114 for any of the locations in profiledregion 110 registered to regional profile database 116 to developrecommendation information 144 to deliver to users of one or more mobiledevices 102, to users of Web browsers connected to the Internet or otherpublic or private networks, or to other users interested in receivinginformation regarding a region of interest, according to variouscriteria and discovery processes described herein. In one or moreaspects, recommendation information 144 can comprise a set ofrecommended locations 280, such as and merely illustratively a sportsarena 258 (labeled “sports arena 1”) and a restaurant 254 (labeled“restaurant 1”) selected from the set of points of interest 112, asshown in FIG. 3. In one or more aspects, locations or places that do notqualify for selection based on user profile 118, regional profile 190,and/or other filtering criteria can be excluded from set of recommendedlocations 280 or other recommendation information 144. In one or moreaspects, locations or places located outside profiled region 110, suchas the illustrated features of whitewater rapids 276 and ski resort 278,can be excluded from the regional profile 190 and/or recommendationinformation 144, based on region parameters used to define or encompassprofiled region 110.

In one or more aspects of the present teachings, and as for instanceillustrated in FIG. 4, the exchange of various sets of geotag data 114and associated information for a profiled region 110 can occur in bothdirections to and from mobile device 102, base station 106, andprofiling server 170 with its associated resources. In one or moreaspects, a user of mobile device 102 can therefore, in addition toreceiving recommendation information 144 via recommendation selector 148or other interface, likewise transmit or upload geotag information tobase station 106 for inclusion in regional profile database 116. The setof geotag data 114 uploaded by the user of mobile device 102 can beregistered and stored to regional profile database 116, incorporated inregional profile 190, and ultimately, in recommendation information 144sent to the user him or herself as well as other users.

In one or more aspects as shown, a set of geotag inputs 108 received inor via mobile device 102 can include attributes or data be entered via auser dialog presented on user interface 104 of mobile device for a usertraveling in, toward, or outside a profiled region. In one or moreaspects as shown, a user can be prompted to add a new set of geotaginputs 108 to be incorporated in a set of geotag data 114, andultimately uploaded to a base station 106 or other destination via awireless interface, such as a cellular telephone or wireless dataconnection. In one or more aspects, the prompts can query or prompt theuser to enter a new set of geotag data 114 (which can be referred as atag, “placemark,” or other term) associated with a location captured bylocation module 106 and reflected in device location data 146. Devicelocation data 146, as noted, can be or include for instancelatitude/longitude coordinates reported by a Global Positioning System(GPS) fix, or other geographic or positional identifiers or data.

In one or more aspects as likewise shown in FIG. 4, set of geotag inputs108 can include selectable category tags (illustratively shown as“restaurant” with a subcategory of “Mexican”, or othercategories/subcategories), a user-entered name for the geotag data, arating dialog, a new tag(s) dialog to enter new or additional tagdescriptors, selected categories, user-entered comments (regarding,e.g., service, location, quality, value, etc), and/or other attributes,fields or data. In one or more aspects, set of geotag inputs 108 canalso or instead include other information than textual or numericalrating information, such as, for instance, audio data such as user voiceannotations or audio samples from a location, video clips or data takenfrom a location, digital still images, or other content. Set of geotaginputs 108 can likewise include, for example, a link, comment, blog, orother information inputted by the user for the associated geographiclocation. Attributes included in set of geotag inputs 108 can alsoinclude the user's name, a time when the user visited the geographiclocation, and/or a time duration of the user's visit to the associatedgeographic location. In one or more aspects, attributes of these typescan be stored in or with the set of geotag inputs 108 and resulting setof geotag data 114 as searchable data fields. When the mobile device 102receives an indication that the set of geotag inputs 108 are ready to bestored, such as when the user submits the set of geotag inputs 108 via akeypad of mobile device 102, the mobile device 102 can upload thoseinputs and any associated data as a set of geotag data 114 to basestation 106 and then profiling server 170, or other destination. Thoseinputs can be entered into regional profile database 116 via profilemodule 136 of profiling server 170 for incorporation in regional profile190. In one or more implementations, the mobile device 102 can also orinstead store the generated set of geotag data 114 directly in localstorage or memory locate in mobile device 102 itself, or in otherlocations.

It may be noted that in one or more implementations, in terms of sharingset of geotag inputs 108 and other data with profiling server 170 orother resources, the user can be provided with a set of privacy controlsto permit the user to share their location history and related data withdesired individuals, such as designated friends. A user may be presentedwith options to filter the visibility of other geotag data, such as torestrict the display to relative distances rather than actual location,to restrict the display to mobility or behavior patterns (e.g., workuntil 6:00 pm) rather than actual location, applying time-based accessrules, or enforcing other privacy or access privileges or restrictions.

FIG. 5 illustrates a flow diagram of various analytic and discoveryprocesses that can be used to generate regional profile 190 from whichrecommendation information 144 can be derived, according to one or moreaspects of the present teachings. In 504, a regional profile 190 for aprofiled region 110 can be created or accessed via regional profiledatabase 116 or other data store or source. In 506, a tag cloud can becomputed for profiled region 110, in which sets of fields or attributesin set of geotag data 114 can be identified and organized for thevarious locations in profiled region 110, along with the frequency ofthose fields or attributes. In 508, processing can be initiated tocompare the resulting geotag cloud and/or other data in regional profile190 associated with profiled region 110 to a list of known regionalprofiles. The list or collection of known regional profiles can containfrequencies and types of attributes contained in respective collectivesets of geotag data 114 for regions of different overall type. Forinstance, known regional profiles can reflect a region whose attributesand related features generally relate to residential areas, commercialareas, resort areas, recreational areas, restaurant areas, nightclub ornightlife areas, and the like. A list or collection of known regionalprofiles can be retrieved from, hosted, or stored in regional profiledatabase 116, or other local or remote data stores. In 510, adetermination can be made whether profiled region 110 matches a knownresidential profile or template. The determination can consist of orinclude determining a frequency and/or threshold of different types oftags (e.g., at least 70% residential), or combinations of tags (e.g.,residential plus home address). If the determination of 510 is yes,processing can proceed to 516 where profiled region 110 can be assigneda matched regional profile 190 indicating a residential categorization,after which processing can proceed to 512. If the determination in 510is no, processing can proceed directly to 512. In 512, a determinationcan be made whether profiled region 110 matches a known commercialprofile or template, using similar techniques. If the determination isyes, processing can proceed to 516 where profiled region 110 can beassigned a matched regional profile 190 indicating a commercialcategorization, after which processing can proceed to 514. If thedetermination in 512 is no, processing can proceed directly to 514.

In 514, a determination can be made whether profiled region 110 matchesany other known profile or template, using similar techniques. If thedetermination is yes, processing can proceed to 516 where profiledregion 110 can be assigned a matched regional profile 190 indicating acorresponding further categorization, after which processing can proceedto 518. If the determination in 514 is no, processing can proceeddirectly to 518. In 518, profile module 136 can compute a set of matchscores for each known profile against which the attributes of profiledregion 110 is compared. For instance, matches can be rated on a scale of0 to 1, or other ranges or confidence levels. In 520, a set of possiblematches for regional profile types for profiled region 110 can beidentified based on the match scores of 520. In one or more aspects, amatch score threshold can be applied, for instance 90% confidence orother criteria, to assign a regional profile type to profiled region 110and store that assignment to regional profile 190 in regional profiledatabase 116. In 522, processing can repeat, return to a priorprocessing point, jump to a further processing point, or end. It may benoted that depending on match values or other factors, more than oneoverall type can be assigned to a profiled region 110.

In one or more aspects, once a regional profile 190 is developed andstored for a subject profiled region 110, in one or more aspects,profile module 136 can leverage the known characteristics of a givenprofiled region 110 to identify an additional region or regions thatdemonstrate a similar profile to the originally profiled region 110 ofinterest. FIG. 6 illustrates a flow diagram of processing for generatingan identification of a similar region to a subject profiled region 110,according to one aspect. In 602, processing can begin. In 604, aregional profile 190 of a given profiled region 110 can be generated,for instance, using processing illustrated in FIG. 5 or otherwise. In606, profile module 136 can compute the profile of one or moreadditional target regions to use to compare against the regional profile190 of profiled region 110.

In 608, profile module 136 can locate one or more profiles within theone or more additional target regions to locate any regions that matchthe regional profile 190 of profiled region 110. In one or more aspects,matching can be performed by matching a minimum number of attributes orfields in the collective sets of geotag data 114 for locations inprofiled region 110 against comparative regions in the set of identifiedadditional target regions. For instance, two regions can be considered ahigh-level match if both are categorized as “residential” at the highestlevel of classification. In 610, profile module 136 can further comparethe additional target regions to determine the most similar region orregions to profiled region 110 available. For instance, two regionsclassified as “residential’ at the highest level can be further comparedto identify the mutual presence of schools, libraries, parks, and/orother locations, places, or features. In 612, the most similar targetregion or region based on the comparative results can be returned as themost similar region(s) to the subject profiled region 110 whose regionallikeness is being sought. In one or more aspects, the next-most similar,or other rankings or numbers of matched target regions can be returned.In 618, processing can repeat, return to a prior processing point, jumpto a further processing point, or end.

In one or more aspects of the present teachings in further regards,besides executing a discovery process to locate similar regions on aregional level, the user of mobile device 102 may wish to locate oridentify individual locations that exhibit similarity to each other,within the boundaries of a destination region. In this regard, theregional profile 190 of the region of the user's immediate vicinity, orother destination region, can be accessed to determine whether otherlocations or places reflect a similar set of characteristics. Forinstance, if a user is experiencing a long wait at a pub in London,England, and would like to locate a similar establishment nearby, theuser of mobile device 102 can request a list or map of “places likehere” displaying similar attributes within the metropolitan area. Thesimilar locations can be restricted to destination regions withinnext-nearest streets, blocks, towns, or other geographic distances orareas. The results for similar locations can be filtered by additionalfactors such as a user profile 118, profiles, or current locations offriends or members of other social groups, or other criteria.

FIG. 7 illustrates a flow diagram of processing to locate similarlocations within a profiled region 110. In 702, processing can begin. In704, one or more set of geotag data 114 including tags, ratings,profiles, and other fields or data for a present location or place in aprofiled region 110 can be retrieved, for instance, from regionalprofile database 116. In 706, the collective sets of geotag data 114including tags, ratings, profiles, and other fields or data foradditional locations or places for a destination region can beretrieved, also for instance from regional profile database 116. In oneor more aspects, the destination region can be the profiled region 110in which the user is currently located.

In 708, profile module 136 can find or identify one or more location orplace in the destination region that represent the closest match to thecurrent location, based on tags, ratings, profiles, or other fields ordata for each candidate location compared to the same or similarattributes for the current location. In one or more aspects, profilemodule 136 can transmit the most similar place to the current locationto mobile device 102 or other client or destination as recommendationinformation 144. In 710, processing can repeat, return to a priorprocessing point, jump to a further processing point, or end. Accordingto one or more aspects in some regards, a user who finds that they enjoyor appreciate a current location or site can thereby receiverecommendation information 144 suggesting other locations of similartype within profiled region 110, among other outputs. It may be notedthat in one or more aspects, initiation of similar-location processingcan be initiated by request of user of mobile device 102, by profilemodule 136 on a predetermined or event-triggered basis, or based onother events or conditions.

In one or more aspects of the present teachings, in certain regards, auser of mobile device 102 may request a suggestion or recommendation ofwhere to go within a profiled region 110 from profile module 136 ofprofiling server 170, or other logic. FIG. 8 illustrates a flow diagramof processing to identify a recommendation for a location to visit orfrequent in profiled region 110. In 802, processing can begin. In 804,profile module 136 can access a set of data for discriminating asuggested location to visit, including a set of hotspots for friends inprofiled region 110, and a set of hotspots for friends in profiledregion 110 filtered based on time of day, hotspots for the overallcommunity of profiled region 110, and hotspots for overall community ofprofiled region 110 filtered by time of day. The set of data canlikewise include a user profile 118 for the user of mobile device 102including designated favorite places, profiles of friends of the user ofmobile device 102 including designated favorite places, and regionalprofile 190 for the subject profiled region 110. In one or more aspects,profiles or other data for friends or other associates of the user ofmobile device 102 can be acquired via a social networking service,including ratings, recommendations, location histories, and otherinformation for the user's friends or other social group.

In terms of generating hotspot data, one or more hotspots in a profiledregion 110 can be generated by profile module 136 by identifying whichlocations within profiled region 110 have been visited or rated by userswithin a predetermined period of time, such as the last week, lastmonth, or other period. In one or more aspects, it may be noted thatprofiling server 170 can maintain or serve a list or map of hotspots andpopular locations, based on the regional profile database 190. In one ormore implementations in this regard, the profile module 136 candetermine a distribution of all user locations at a given time orinterval. For example, the profile module 136 can determine that it is6:00 pm, and the user is currently within a given profiled region 110,such as within ZIP code 95008. The profile module 136 can determine thatat that time, the distribution of all users of mobile devices registeredto the server network is 50% downtown, 20% at home, 10% at a publicpavilion, 10% at a shopping mall, and 10% unknown. In one or moreaspects, details can be zoomed at a particular location to determine areason for a population of users congregating within a profiled region110, for example a public concert in a park or other area. Thedistribution of locations can be filtered by or analyzed in terms oftime-of-day or other scheduling bands, such as lunch time, dinner time,commute time, or other intervals of common activity. Day of week, monthof year, holiday, or other information can also be used to inform theanalysis of collective user positions. Again, social group profiles andpersonal preferences can also be used to filter hot spot or popularlocation hits.

Returning to the processing flow, in 806, profile module 136 can matchor sort a set of locations or places in the regional profile 190 of theprofiled region 110 using the profiles of the user's friends, hotspotratings, or data, set of geotag data 114 for regional profile 190,and/or user profile 118. For instance, profile module 136 can identifythose locations in profiled region 110 whose overall relevance orpotential level of interest to the user are the greatest, next-greatest,and so forth in order. Overall relevance can be determined, for example,by rating or weighting the number of matches in set of geotag data 114for each candidate location against the profile, hotspot, or othercomparative attributes. In 808, profile module 136 can generate a set ofrecommendation information 144, sorted by degree of relevance, totransmit to the user of mobile device 102. For instance, recommendationinformation 144 can include a list of Mexican restaurants mostfrequently visited and/or most highly rated by the user's set offriends, by other users at large in the community, most visited by theuser in the past, or based on other criteria. In 8120, processing canrepeat, return to a prior processing point, jump to a further processingpoint, or end.

In terms of generating a user profile 118 for use in discovery orsearching against the set of geotag data 114 stored in regional profile190, as noted, a variety of user-supplied and/or network-generated datacan be used to develop a set of preferences, selections, histories,and/or other data to build user profile 118 for a user of mobile device102. FIG. 9 illustrates a variety of sets of user-related data that canbe accessed or received as inputs by profile module 136 to generate andoutput user profile 118. Those inputs, as illustratively shown, caninclude a set of favorite places 120 associated with the user. Set offavorite places 120 can include places which the user explicitly entersor designates as favorite locations, and in addition or instead caninclude locations identified through analysis of the location history orother records of activity for that user. The inputs, as likewiseillustratively shown, can include user tagging data 122 indicating tagsor other inputs that the user has supplied as part of one or more set ofgeotag data 114 for locations in the past. For instance, a user whofrequently inputs or uploads ratings of golf courses or pro shops can beinferred to have a greater than average interest in golf activities, anduser profile 118 can include a category tag of “golf” for potentiallyfavorite locations.

The inputs to a user profile 118, as similarly shown in FIG. 9, can alsoinclude the regional profile 190 for any one or more profiled region 110in which the user has designated a favorite location or place. Theinputs to user profile 118, as likewise shown, can also include a set offriend user profiles 126 for a set of friends for the user. In one ormore aspects, those profiles or other data can be imported or receivedform a social networking service. In one or more aspects, a set of otheruser attributes 270 can likewise be incorporated into the inputs toprofile module 136 to generate user profile 118. It may be noted that Inone or more aspects, different inputs accepted by profile module 136 togenerate user profile 118 can be weighted or used differently, forinstance, based on the differing predictive power of various inputs.Thus, in one or more aspects, prior location or transaction history forthe user of mobile device 102 can be accorded greater weight than thesame histories of users in set of friend user profiles 126. User profile118 can, again, include data indicating favorite locations for the user,a location or transaction history for the user, category tags for areasor activities of interest to the user, and/or other data. In one or moreaspects, profile module 136 can update user profile 118 at varioustimes, such as at predetermined intervals, or based on triggering eventssuch as user entry of new geotag data. In one or more aspects again,user profile 118 can in addition or instead include data or preferencesentered directly by the user.

In one or more aspects of the present teachings in further regards, theuser of mobile device 102 can request and/or profile module 136 candetermine a set of recommendations for one or more new places for theuser to visit in a profiled region 110. That is, the user can requestand/or the profiling server 170 on a predetermined basis can decide togenerate a set of previously unvisited locations for the user to receiveas potential sites of interest to the user. FIG. 10 illustrates a flowdiagram of processing to identify potential new places of interest for auser to visit or frequent. In 1002, processing can begin. In one or moreaspects, processing to generate a recommendation of a new place for theuser to visit can be initiated, for instance, via a user-initiatedrequest and/or initiation by the network. In 1004, profile module 136 orother logic can access data sets to develop suggested new places. Thosedata sets as shown can include a list of locations or places in aprofiled region 110, any designated user favorite places in profiledregion 110 or elsewhere recorded in user profile 118 or other record,any identified hotspot(s) in profiled region 110 including friend-basedor community-wide hotspots, any favorite locations designated by friendsof the user such as social networking members and places tagged orrecommended by them, and/or other data associated with a profiled region110.

In 1006, profile module 136 can remove any locations or places which theuser has already designated as a favorite place in user profile 118 orotherwise, to ensure any suggested locations represent new or previouslyunvisited places to the user. In 1008, the set of remaining places canbe sorted by profile module 136 or other logic based on selectedpriorities or weightings used to order the resulting set of potentialnew places. For instance, places displaying a higher hotspot rating bymembers of the user's social networking service can be given greaterweight than community-wide hotspots. In one or more aspects, the sortingof potential new places can likewise be adapted based on time of dayinformation. In 1010, a set of new recommended places can be generatedas part of a set of recommendation information 144 to be transmitted tomobile device 102 or otherwise. In 1012, processing can repeat, returnto a prior processing point, jump to a further processing point, or end.

In one or more aspects of the present teachings in still furtherregards, besides including potential new places in recommendationinformation 144, profile module 136 can leverage the informationcontained in regional profile 190 to develop user profiles to recommendor present to an existing user, business operator, marketingorganization, or others, using linkages or similarities to attributes ofrecommended new locations for the user(s). One feature of this type ofrecommendation is that it permits an identification of users who may bemore likely to visit a location. FIG. 11 illustrates a flow diagram ofprocessing to develop recommendation information 144, including userprofiles affiliated or linked with one or more profiled region 110. In1102, processing can begin. In 1104, profile module 136 can identify oneor more additional profiled region 110 having an associated regionalprofile 190 that matches, is similar to, or otherwise correlated with arecommended new location or place. In one or more aspects, a suggestednew location in 1104 can be identified using processing illustrated inFIG. 10, or other techniques. For instance, if the new location is anoceanside recreational area such as a beach or boardwalk, profile module136 can locate one or more additional profiled region 110 that containsa tag “ocean” in set of geotag data 114 or otherwise indicates oceansidesites in the respective points of interest 112.

In 1106, profile module 136 can identify individual locations or siteswithin each additional profiled region 110 that contain similarattributes to the identified new location. In one or more aspects,profile module 136 can search the set of geotag data 114 for locationsin each of the one or more additional profiled region 110 that matchesattributes of the new location, such as a tag containing “surf park.” In1108, profile module 136 can identify one or more user profile 118associated with the matching locations that correspond to or match theattributes of the new location. Thus for instance, user attributes,preferences, or other tags or data that indicate an interest in“snorkeling,” “surfing,” “sailing” and so forth can be identified asmatching or related to new location that is an oceanside recreationalarea. In 1110, profile module 136 can identify a subset of the one ormore user profiles 118 generated in this fashion that match orcorrespond to user profile 118 for the user to whom the new location wasrecommended. For instance, attributes that match in favorite locations,preferred interests, and the like can be used to identify one or moreuser profile 118 that is similar to that of the user of mobile device102 receiving a recommendation of a new location. In one or moreaspects, the one or more user profile 118 that is identified as similarcan for instance be transmitted or presented to a business operatorwhose location relates to the matching attributes. In one or moreaspects, the information can be transmitted to the user of mobile device102, for instance to extend invitations to social networks or importfavorite locations or other attributes related to set of geotag data114. In 1112, processing can repeat, return to a prior processing point,jump to a further processing point, or end.

According to one or more aspects in yet further regards, it may be notedthat in general, set of geotag data 114 associated with a place orlocation, region, or other geographic area can be encoded in a varietyof forms, including in the form of speech samples or annotations, orother audio data supplied by a user related to a location or region. Inone or more implementations, the speech input can require the user touse a defined vocabulary of input words or terms. In one or moreimplementations, the mobile device and/or the geotag server can alsodetermine commonly used geotag vocabulary by the user or a group ofusers, to train and improve speech recognition capability. In one ormore implementations, the speech processing used to extract geotaginformation can rely upon natural language processing to automaticallyextract intended tag or other information from unrestricted speechpatterns. In one or more implementations, the speech pattern of a givenuser and/or other users, as well as patterns in tags surrounding thesubject location be tagged can be analyzed, to dynamically create arecognition grammar. In one or more implementations, these types ofdynamically generated grammar can be generated for each recognitionrequest.

For instance, a user visiting a national park may activate a voicerecording feature on their mobile device 102, and speak into the deviceto record remarks, tags, or other data, such as “clear ocean view” or“large camping facilities.” In one or more aspects in these regards,profile module 136, mobile device 102, and/or other hardware or otherresources can be equipped with speech processing circuitry and/or logicto capture and analyze voice, speech, or audio content as part of set ofgeotag data 144. In one or more aspects (for example as shown in FIG. 15described below), mobile device 102 can be equipped with a speech module288 for these and other purposes. In one or more aspects (for example asshown in FIG. 16 described below), profiling server 170 can also orinstead be equipped with a speech module 298 for these and otherpurposes.

FIG. 12 illustrates a flow diagram of processing to analyze and addvoice-annotated tags, comments, or other data as part of set of geotagdata 114 in regional profile database 116, according to one or moreimplementations. In 1202, processing can begin. In 1204, an encodedvoice clip can be received from or via mobile device 102. In one or moreaspects, voice data can be received along with additional attributessuch as a profile name for a regional profile 190 and/or other profileor data record. In one or more aspects, the corresponding encoded voiceclip or sample can be received in profile module 136 of profiling server170 via speech module 298, in a processor or storage of mobile device102 itself, via speech module 288, or in other processor, memory, orstorage resources. In one or more aspects, the encoded can be recordedin a variety of media formats or encoding schemes, such as pulse codemodulated (PCM), MP3 (Motion Pictures Expert Group Layer 3), or otherformat. In 1206, the encoded voice clip can be decoded and properties ofthe voice clip can be extracted. For instance, the sampling rate (e.g.44.1 kHz), number of channels (e.g. mono or stereo), bits per sample(e.g. 16 bits), compression techniques, dithering settings, and/or otherconfiguration details for the audio sample can be registered oridentified.

In 1208, a voice recognition engine, audio codec, or other speech modulecan be created, accessed, and/or reused with corresponding settings asthose detected in 1206 (e.g., sampling rate, number of channels, bitdepth, and so forth). In 1210, the voice recognition engine, audiocodec, or other speech module can be invoked or instantiated, forinstance, by initiating software programming in profiling server 170. In1212, the text result produced by executing speech recognition againstaudio clips or samples inputted in set of geotag data 114 can be parsed,for instance to extract tags, categories, comments, sentences, and/orother linguistic or textual output. In 1214, the place description of alocation or place in a set of points of interest 112 in a profiledregion 110 associated with the voice annotation can be augmented toreflect the decoded voice data. For instance, the set of geotag data 114associated with a given place, location, or region can be augmented bydata fields such as the user's name, any tags the user has assigned tothe data, any user ratings contained in the speech input, commentsidentified in the speech input, and/or other fields or data. In 1216,the augmented place description containing the user-supplied spokenattributes can be submitted or transmitted to profiling server 170 aspart of a set of geotag data 114, for instance for incorporation inregional profile 190. In one or more implementations, the voice or audiosample itself can be stored to regional profile database 116, forinstance for potential replay, if desired. In 1218, processing canrepeat, return to a prior processing point, jump to a further processingpoint, or end.

In terms of performing speech recognition during processing shown inFIG. 12 or otherwise, in one or more aspects, speech module 288, speechmodule 298, profile module 136, or other logic can employ specializedspeech recognition to more accurately or efficiently identify tags andother attributes in set of geotag data 114 supplied by a user of mobiledevice 102. More particularly, speech module 288 in mobile device 102,speech module 298 in profiling server 170, or other logic can accessspeech training sets that are associated with a profiled region 110and/or one of its constituent locations, to generate a customizedtraining set 158 (as shown e.g. in FIG. 15 and FIG. 16 when hosted inmobile device 102 and profiling server 170, respectively) that allowsgreater recognition of potentially significant tags, words, or otherterms or speech components.

In one or more aspects in these regards, FIG. 13 illustrates a flowdiagram of processing that can be used to identify voice tag data usingcustomized or specialized training sets for voice recognition. In 1302,processing can begin. In 1304, a voice recognition engine, audio codec,or other speech module, for instance in profiling server 170 and/or inmobile device 102, can initiate speech recognition processing byidentifying an initial frequency of speech unit sequences for use as aspeech decoding dictionary, such as an ordered set of N-grams. In one ormore aspects, the speech unit sequences can consist of an N-gram, or aset of words which appear in a given order, such as “Mexican restaurantwithin 10 miles.” In 1306, a frequency of speech unit sequences can bedetermined for all users around a location having a voice tag containedin set of geotag data 114. In 1308, a frequency of speech unit sequencescan be determined for speech samples ever spoken by the subject user. In1310, a frequency of tags in a surrounding area (or tag “cloud”)associated with a specific subject location can be determined. Forexample, a given location in profiled region 110 with definedlatitude/longitude coordinates (or, latitude/longitude/altitudecoordinates) can have the term “golf” appearing in the associated set ofgeotag data 114 with a frequency above a predetermined threshold.

In 1312, a customized training set 158 can be generated reflecting thefrequency of speech unit sequences to be used in a grammar forrecognizing voice data elements supplied by the user at the subjectlocation of interest, based on the frequencies calculated or identifiedin the speech unit sequences of 1304-1310. In one or more aspects, thevarious speech unit sequences can be given different weights or valuesfor speech recognition purposes. For instance, speech unit sequencesextracted from the user him or herself can be given greater weightrelative to any initial or default frequencies, and/or relative tosequences of other users. The customized training set 158 can provide amore accurate and more efficient set of speech unit sequences andresulting word recognition, as a result. In 1314, processing can repeat,return to a prior processing point, jump to a further processing point,or end. In one or more aspects, the customized training set 158generated as described can be updated, for instance on a regular orevent-triggered basis.

As described herein, one type of output produced by the regionalprofiling activity carried out by profile module 136 on set of geotagdata 114 and other information can be or include a set of recommendationinformation 144, reflecting a matching of potential user interests andfeatures or attractions in a profiled region 110. In one or more aspectsof the present teachings in further regards, and as for instanceillustrated in FIGS. 14A and 14B, profile module 136 can generate adynamically ordered menu (e.g. shown as 140 and 340 in FIG. 14A, and 140in FIG. 14B), or other adaptive representation of recommendationinformation 144. Dynamically ordered menu 140 (or 340) can presentcategories of recommendation information 144 based on the user profile118 of the user of mobile device 102, and/or other filters or criteria.In one or more aspects as shown, for instance, in FIG. 14A,recommendation information 144 can be received in mobile device 102 of afirst user and mobile device 302 of a second user, both located in thesame location in a profiled region 110. In one or more aspects as shown,the recommendation information 144 generated for the respective users ofthe two devices can be presented to those users via user interface 104and 304 in the form of a (first) dynamically ordered menu 140 and(second) dynamically ordered menu 340, respectively. In one or moreaspects, profile module 136 or other logic can process recommendationinformation 144 to apply logic to the presentation order of recommendedlocations or other data for each user. The order of categories of otherselections or data in (first) dynamically ordered menu 140 and (second)dynamically ordered menu 340 or other dialog can, for instance, be,based on their respective user profiles 118 or other data to generatethe two separate lists appearing in dynamically ordered menu 140 anddynamically ordered menu 340 presented to each respective user.

In one or more aspects as shown, even though both users or located inthe same or substantially same location or place (illustratively, thecity of Miami, Fla.) having the same surrounding set of points ofinterest 112, the dynamically ordered menu 140 for the first user canpresent a different set of categories for selection compared to thedynamically ordered menu 340 for the second user. Again asillustratively shown, if the user profile 118 of the first user forinstance indicates a preference for watersports or related sites oractivities, the first category of recommended sites contained indynamically ordered menu 140 can be watersports, which can include orexpand into locations such as a sea park 350 and boat tour 352. Thefirst or preferred category for that user can be followed by a secondcategory, illustratively restaurants. Conversely, and as likewise shown,if the user profile 118 of the second user for instance indicates apreference for restaurants, the first category in dynamically orderedmenu 340 for that user can include or expand into locations such as aCuban restaurant 356 and seafood restaurant 358, followed by a categoryfor watersports, and so forth.

In one or more aspects, the dynamically ordered menu 140 and dynamicallyordered menu 340 can be adapted based on other factors in addition to orinstead of user profile 118 coupled with regional profile 190, such as,for instance, the current location or presence of friends in a socialnetworking group within profiled region 110, current or expected weatherconditions that may affect preferred activities or sites, or othervariables or criteria. For instance, In one or more aspects dynamicallyordered menu 140 or dynamically ordered menu 340 can be sorted orreordered based on scheduling factors such as time of day, day of week,or month of year, with recreational recommendations for instance takingprecedence or receiving greater weight during weekend or holiday periodsas compared to business working days.

Likewise, and as shown for instance in FIG. 14B, in one or more aspects,dynamically ordered menu 140 can be ordered in different ways for thesame user of mobile device 102 as that user travels from a firstprofiled region 110 to an illustrative second profiled region 380. Inone or more aspects as shown, while located in profiled region 110,illustratively indicated as the city of Charleston, S.C., thedynamically ordered menu 140 can list a first category of golf, whichcan include or expand into golf course 362 (illustratively labeled “golfcourse 1”) and golf course 364 (illustratively labeled “golf course 2”),followed by a second category of hotels. The dynamically ordered menu140 for that location can be filtered by user profile 118 including, forinstance, tag or preference data indicating an interest in golf sitesand local accommodations. After traveling to a second profiled region380, illustratively indicated as the city of Atlanta, Ga., thedynamically ordered menu 140 for the same user can list a set ofcategories for recommended places include a category of hotels which caninclude or expand into hotel 376 (illustratively labeled “hotel 1”) andhotel 374 (illustratively labeled “hotel 2”), followed by categories forlocal festivals, golf, and so forth. In one or more aspects, thecategories of recommendation information presented in dynamicallyordered menu 140 for the same user at the second location can indicate adifferent set, order, or sequence of recommendations, based on userprofile 118 or other criteria. For instance, user profile 118 canindicate that a user preference for golf courses, but that the userranks those of first interest only if the available courses exceed 5000yards in length, or satisfy other criteria. Other variables can be usedto generate categories or other user selections in dynamically orderedmenu 140 for the same user in the same or different places, including,for example, time of day, day of week, month, or other time or otherschedule-related information.

FIG. 15 illustrates an exemplary configuration of hardware, software,and other resources of a mobile device 102, consistent with one or moreimplementations of the present teachings. Mobile device 102 can includeat least one antenna 702 (e.g., a transmission receiver or group of suchreceivers comprising an input interface, etc.) that receives a signal(e.g., pertaining to a mobile call initiation or other handshake, ahandshake response, a mobile application data transfer, a data event,data event response, handshake termination, and so on) and a receiver704, which performs actions (e.g., filters, amplifies, down-converts,etc.) on the received signal. Antenna 702 can be further coupled to atransmitter 718 to transmit signals. Antenna 702 can for exampletransmit or receive a response to a handshake request, data eventrequest, or the like. Transmitted signals can be or include a set oflocation fixes 130, and other data, as described herein. Antenna 702 andreceiver 704 can also be coupled with a demodulator 706 that candemodulate received signals and provide the demodulated information to aprocessor 708 for processing. Mobile device 102 can additionally includememory 710 that is coupled to processor 708 and that can store data tobe transmitted, received, and the like.

Processor 708 can analyze information received by antenna 702 and/or auser interface 104 of the mobile device 102 and/or generate informationfor transmission by a transmitter 718 via a modulator 716. Additionally,processor 708 can control and/or access one or more resources orcomponents (e.g., 706, 712, 714, 716, 718) of the mobile device 102.Processor 708 can execute a runtime environment 712, such as BREW®available from Qualcomm Incorporated, as well as one or more set ofapplications 714 or other software, modules, applications, logic, code,or the like. Processor 708 can communicate with a location module 106,such as a Global Positioning System (GPS) module or chip, to receive andprocess location-related information, including device location data146. Processor 708 can further communicate with a location API(Application Programming Interface) 720 to execute function calls toextract location information, regional profile data, and generaterecommendation information according to the present teachings. In one ormore implementations, mobile device 102 can optionally incorporate aspeech module 288 such as a digital to analog (DAC) chip, digital signalprocessing chip, software applications, and/or other resources toprocess speech input and other audio data. When present, processor 708can also communicate with a speech module 288 to process audio samplesand other data. Processor 708 can likewise couple with user interface104, such as a graphical user interface or other graphical display, todisplay graphics, video, location-based information includingrecommendation information 144, and other information.

FIG. 16 illustrates an exemplary set of hardware, software, and otherresources that can be incorporated in, maintained by, or associated withprofiling server 170, and associated network resources and components,according to various implementations. Profiling server 170 can include,access, or communicate with a receiver 810 that receives signal(s) fromone or more mobile device 102 through a plurality of receive antennas806, and a transmitter 822 that transmits to the one or more mobiledevice 102 through a transmit antenna 808. Receiver 810 can receiveinformation from receive antennas 806 and be operatively coupled with ademodulator 812 that demodulates received information. A processor 814can analyze demodulated signals provided by demodulator 812. Theprocessor 814 further couples to a memory 816 that can store one or moreapplication 818 that can execute, support, facilitate and/or participatein communication and profiling activities as described herein. Processor814 can likewise couple with a profile module 136 to capture, manage,store, and transmit device location data 146, recommendation information144, and other information, as described herein. In one or moreimplementations, profiling server 170 can optionally incorporate aspeech module 298 such as a digital to analog (DAC) chip, digital signalprocessing chip, software applications, and/or other resources toprocess speech input and other audio data. When present, processor 814can also communicate with a speech module 298 to process audio samplesand other data. Processor 814 can in addition communicate with a networkinterface 822, such as an Ethernet or other wired, optical, or wirelessinterface, to communicate with other network links or resources, such asa cellular or other air interface. In one or more implementations,processor 814 and associated resources can be hosted in a wirelessserver. In one or more implementations, profiling server 170 can beco-hosted, and/or located separately or remotely from base station 106.In one or more implementations, multiple or distributed servers orprocessors can be used.

The foregoing description is illustrative, and variations inconfiguration and implementation may occur to persons skilled in theart. For instance, the various illustrative logics, logical blocks,modules, and circuits described in connection with the implementationsdisclosed herein may be implemented or performed with a general purposeprocessor, a digital signal processor (DSP), an application specificintegrated circuit (ASIC), a field programmable gate array (FPGA) orother programmable logic device, discrete gate or transistor logic,discrete hardware components, or any combination thereof designed toperform the functions described herein. A general-purpose processor maybe a microprocessor, but, in the alternative, the processor may be anyconventional processor, controller, microcontroller, or state machine. Aprocessor may also be implemented as a combination of computing devices,e.g., a combination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other such configuration. In one or more exemplaryimplementations, the functions described may be implemented in hardware,software, firmware, or any combination thereof. If implemented insoftware, the functions may be stored on or transmitted over as one ormore instructions or code on a computer-readable medium.Computer-readable media includes both computer storage media andcommunication media including any medium that facilitates transfer of acomputer program from one place to another. A storage media may be anyavailable media that can be accessed by a computer. By way of example,and not limitation, such computer-readable media can comprise RAM, ROM,EEPROM, CD-ROM or other optical disk storage, magnetic disk storage orother magnetic storage devices, or any other medium that can be used tocarry or store desired program code in the form of instructions or datastructures and that can be accessed by a computer. Also, any connectionis properly termed a computer-readable medium. For example, if thesoftware is transmitted from a website, server, or other remote sourceusing a coaxial cable, fiber optic cable, twisted pair, digitalsubscriber line (DSL), or wireless technologies such as infrared, radio,and microwave, then the coaxial cable, fiber optic cable, twisted pair,DSL, or wireless technologies such as infrared, radio, and microwave areincluded in the definition of medium. Disk and disc, as used herein,includes compact disc (CD), laser disc, optical disc, digital versatiledisc (DVD), floppy disk, and blu-ray disc where disks usually reproducedata magnetically, while discs reproduce data optically with lasers.Combinations of the above should also be included within the scope ofcomputer-readable media. The steps of a method or algorithm described inconnection with the implementations disclosed herein may be embodieddirectly in hardware, in a software module executed by a processor, orin a combination of the two. A software module may reside in RAM memory,flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a harddisk, a removable disk, a CD-ROM, or any other form of storage mediumknown in the art. An exemplary storage medium is coupled to theprocessor, such that the processor can read information from, and writeinformation to, the storage medium. In the alternative, the storagemedium may be integral to the processor. The processor and the storagemedium may reside in an ASIC. The ASIC may reside in a user terminal. Inthe alternative, the processor and the storage medium may reside asdiscrete components in a user terminal.

The techniques described herein may be used for various wirelesscommunication systems such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA and othersystems. The terms “system” and “network” are often usedinterchangeably. A CDMA system may implement a radio technology such asUniversal Terrestrial Radio Access (UTRA), cdma2000, etc. UTRA includesWideband-CDMA (W-CDMA) and other variants of CDMA. Further, cdma2000covers IS-2000, IS-95, and IS-856 standards. A TDMA system may implementa radio technology such as Global System for Mobile Communications(GSM). An OFDMA system may implement a radio technology such as EvolvedUTRA (E-UTRA), Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE802.16 (WiMAX), IEEE 802.20, Flash-OFDM□, etc. UTRA and E-UTRA are partof Universal Mobile Telecommunication System (UMTS). 3GPP Long TermEvolution (LTE) is a release of UMTS that uses E-UTRA, which employsOFDMA on the downlink and SC-FDMA on the uplink. UTRA, E-UTRA, UMTS,LTE, and GSM are described in documents from an organization named “3rdGeneration Partnership Project” (3GPP). Additionally, cdma2000 and UMBare described in documents from an organization named “3rd GenerationPartnership Project 2” (3GPP2). Further, such wireless communicationsystems may additionally include peer-to-peer (e.g., mobile-to-mobile)ad hoc network systems often using unpaired unlicensed spectrums, 802.xxwireless LAN, BLUETOOTH and any other short- or long-range, wirelesscommunication techniques.

For further example, while aspects have been described in whichprofiling server 170 or other logic responds to sensed data includinglocation device location information 146, user profile 118, and otherdata to generate recommendation information 144, in one or moreimplementations, the user of mobile device 102 can in addition orinstead simply enter a set of search terms to view any locations orplaces which match the query terms in regional profile database 116,with or without other data. For further example, while implementationshave been described in which a single user is tracked via a singlemobile device 102, in one or more implementations the behavior andtagging information for one user can be aggregated from multiple mobiledevices the user may use. Various other resources described as singularor integrated can In one or more implementations be plural ordistributed, and resources described as multiple or distributed can Inone or more implementations be combined. The scope of the presentteachings is accordingly intended to be limited only by the followingclaims.

1. A method of operating a mobile device, comprising: displaying aplurality of categories of recommendations, the plurality of categoriesof recommendations being based on a regional profile of a geographicregion, the regional profile including a set of points of interestwithin the geographic region, wherein the plurality of categories ofrecommendations is different for a first geographic region of aplurality of geographic regions compared to a second geographic regionof the plurality of geographic regions; obtaining a selection of acategory of the plurality of categories of recommendations; displaying,responsive to the obtained category of the plurality of categories ofrecommendations, at least one recommended point of interest from the setof points of interest via a user interface of the mobile device, whereinthe at least one recommended point of interest is displayed based on atleast user ratings of the set of points of interest within thegeographic region, including the at least one recommended point ofinterest; obtaining a selection of a point of interest from among thedisplayed at least one recommended point of interest; and displayinguser-uploaded content associated with the selected point of interest viathe user interface of the mobile device, the user-uploaded contentsubject to privacy controls associated with a set of users that providedthe user-uploaded content.
 2. The method of claim 1, wherein the privacycontrols comprise one or more privacy controls related to locationhistory sharing of at least one user of the set of users.
 3. The methodof claim 1, wherein the privacy controls comprise one or more privacycontrols related to a display of relative distances rather than actuallocations of at least one user of the set of users that provided theuser-uploaded content.
 4. The method of claim 1, wherein the privacycontrols comprise one or more privacy controls related to a display ofmobility or behavior patterns rather than actual locations of at leastone user of the set of users that provided the user-uploaded content. 5.The method of claim 1, wherein the privacy controls comprise one or moreprivacy controls related to time-based access rules associated with asubset of the user-uploaded content provided by at least one user of theset of users.
 6. The method of claim 1, wherein the at least onerecommended point of interest is displayed further based on arecommended time of day for visiting the at least one recommended pointof interest.
 7. The method of claim 1, wherein the at least onerecommended point of interest is displayed further based on the userratings having been generated within a predetermined period of time. 8.The method of claim 1, wherein the user-uploaded media content includes:one or more user-captured images captured at the selected point ofinterest, one or more user-captured video clips captured at the selectedpoint of interest, user-captured audio data captured at the selectedpoint of interest, the user ratings of the set of points of interest, orany combination thereof.
 9. The method of claim 1, further comprising:determining a current location of the mobile device.
 10. The method ofclaim 9, wherein the geographic region includes the current location ofthe mobile device.
 11. A method comprising: obtaining, via a userinterface of a mobile device, a selection of at least one category ofrecommendations of a plurality of categories of recommendations in whichto categorize a point of interest, the plurality of categories ofrecommendations being based on a regional profile of a geographicregion, the regional profile including a set of points of interestwithin the geographic region; obtaining, via the user interface of themobile device, user-uploaded content associated with the point ofinterest; and obtaining, via the user interface of the mobile device, atleast one privacy control associated with the user-uploaded content. 12.The method of claim 11, wherein the at least one privacy controlcomprises one or more privacy controls related to location historysharing of the mobile device.
 13. The method of claim 11, wherein the atleast one privacy control comprises one or more privacy controls relatedto a display of relative distances between the mobile device and thepoint of interest, rather than actual locations of the mobile device.14. The method of claim 11, wherein the at least one privacy controlcomprises one or more privacy controls related to a display of mobilityor behavior patterns of the mobile device relative to the point ofinterest, rather than actual locations of the mobile device.
 15. Themethod of claim 11, wherein the at least one privacy control comprisesone or more privacy controls related to time-based access rulesassociated with the user-uploaded content.
 16. The method of claim 11,further comprising: determining a current location of the mobile device.17. The method of claim 16, further comprising: setting a location ofthe point of interest as the current location of the mobile device. 18.The method of claim 16, further comprising: associating the point ofinterest with a time of day during which the mobile device was locatedat the point of interest.
 19. The method of claim 16, wherein thegeographic region includes the current location of the mobile device.20. The method of claim 11, wherein the user-uploaded media contentincludes: one or more user-captured images captured at the point ofinterest, one or more user-captured video clips captured at the point ofinterest, user-captured audio data captured at the point of interest, auser rating of the point of interest, a time of day during which themobile device was located at the point of interest, or any combinationthereof.
 21. The method of claim 11, wherein the method is performed bythe mobile device.
 22. The method of claim 11, wherein the method isperformed by a server in communication with the mobile device.
 23. Amobile device, comprising: memory configured to store data,instructions, or a combination thereof; and at least one processorcommunicatively coupled to the memory, the at least one processorconfigured to: display a plurality of categories of recommendations, theplurality of categories of recommendations being based on a regionalprofile of a geographic region, the regional profile including a set ofpoints of interest within the geographic region, wherein the pluralityof categories of recommendations is different for a first geographicregion of a plurality of geographic regions compared to a secondgeographic region of the plurality of geographic regions; obtain aselection of a category of the plurality of categories ofrecommendations; display, responsive to the obtained category of theplurality of categories of recommendations, at least one recommendedpoint of interest from the set of points of interest via a userinterface of the mobile device, wherein the at least one recommendedpoint of interest is displayed based on at least user ratings of the setof points of interest within the geographic region, including the atleast one recommended point of interest; obtain a selection of a pointof interest from among the displayed at least one recommended point ofinterest; and display user-uploaded content associated with the selectedpoint of interest via the user interface of the mobile device, theuser-uploaded content subject to privacy controls associated with a setof users that provided the user-uploaded content.
 24. The mobile deviceof claim 23, wherein the privacy controls comprise one or more privacycontrols related to location history sharing of at least one user of theset of users.
 25. The mobile device of claim 23, wherein the privacycontrols comprise one or more privacy controls related to a display ofrelative distances rather than actual locations of at least one user ofthe set of users that provided the user-uploaded content.
 26. The mobiledevice of claim 23, wherein the privacy controls comprise one or moreprivacy controls related to a display of mobility or behavior patternsrather than actual locations of at least one user of the set of usersthat provided the user-uploaded content.
 27. The mobile device of claim23, wherein the privacy controls comprise one or more privacy controlsrelated to time-based access rules associated with a subset of theuser-uploaded content provided by at least one user of the set of users.28. The mobile device of claim 23, wherein the at least one recommendedpoint of interest is displayed further based on a recommended time ofday for visiting the at least one recommended point of interest.
 29. Themobile device of claim 23, wherein the at least one recommended point ofinterest is displayed further based on the user ratings having beengenerated within a predetermined period of time.
 30. The mobile deviceof claim 23, wherein the user-uploaded media content includes: one ormore user-captured images captured at the selected point of interest,one or more user-captured video clips captured at the selected point ofinterest, user-captured audio data captured at the selected point ofinterest, the user ratings of the set of points of interest, or anycombination thereof.
 31. The mobile device of claim 23, wherein the atleast one processor is further configured to: determine a currentlocation of the mobile device.
 32. The mobile device of claim 31,wherein the geographic region includes the current location of themobile device.
 33. An apparatus comprising: memory configured to storedata, instructions, or a combination thereof; and at least one processorcommunicatively coupled to the memory, the at least one processorconfigured to: obtain, via a user interface of a mobile device, aselection of at least one category of recommendations of a plurality ofcategories of recommendations in which to categorize a point ofinterest, the plurality of categories of recommendations being based ona regional profile of a geographic region, the regional profileincluding a set of points of interest within the geographic region;obtain, via the user interface of the mobile device, user-uploadedcontent associated with the point of interest; and obtain, via the userinterface of the mobile device, at least one privacy control associatedwith the user-uploaded content.
 34. The apparatus of claim 33, whereinthe at least one privacy control comprises one or more privacy controlsrelated to location history sharing of the mobile device.
 35. Theapparatus of claim 33, wherein the at least one privacy controlcomprises one or more privacy controls related to a display of relativedistances between the mobile device and the point of interest, ratherthan actual locations of the mobile device.
 36. The apparatus of claim33, wherein the at least one privacy control comprises one or moreprivacy controls related to a display of mobility or behavior patternsof the mobile device relative to the point of interest, rather thanactual locations of the mobile device.
 37. The apparatus of claim 33,wherein the at least one privacy control comprises one or more privacycontrols related to time-based access rules associated with theuser-uploaded content.
 38. The apparatus of claim 33, wherein the atleast one processor is further configured to: determine a currentlocation of the mobile device.
 39. The apparatus of claim 38, whereinthe at least one processor is further configured to: set a location ofthe point of interest as the current location of the mobile device. 40.The apparatus of claim 38, wherein the at least one processor is furtherconfigured to: associate the point of interest with a time of day duringwhich the mobile device was located at the point of interest.
 41. Theapparatus of claim 38, wherein the geographic region includes thecurrent location of the mobile device.
 42. The apparatus of claim 33,wherein the user-uploaded media content includes: one or moreuser-captured images captured at the point of interest, one or moreuser-captured video clips captured at the point of interest,user-captured audio data captured at the point of interest, a userrating of the point of interest, a time of day during which the mobiledevice was located at the point of interest, or any combination thereof.43. The apparatus of claim 33, wherein the apparatus is the mobiledevice.
 44. The apparatus of claim 33, wherein the apparatus is a serverin communication with the mobile device.
 45. A mobile device,comprising: means for displaying a plurality of categories ofrecommendations, the plurality of categories of recommendations beingbased on a regional profile of a geographic region, the regional profileincluding a set of points of interest within the geographic region,wherein the plurality of categories of recommendations is different fora first geographic region of a plurality of geographic regions comparedto a second geographic region of the plurality of geographic regions;means for obtaining a selection of a category of the plurality ofcategories of recommendations; means for displaying, responsive to theobtained category of the plurality of categories of recommendations, atleast one recommended point of interest from the set of points ofinterest via a user interface of the mobile device, wherein the at leastone recommended point of interest is displayed based on at least userratings of the set of points of interest within the geographic region,including the at least one recommended point of interest; means forobtaining a selection of a point of interest from among the displayed atleast one recommended point of interest; and means for displayinguser-uploaded content associated with the selected point of interest viathe user interface of the mobile device, the user-uploaded contentsubject to privacy controls associated with a set of users that providedthe user-uploaded content.
 46. An apparatus comprising: means forobtaining, via a user interface of a mobile device, a selection of atleast one category of recommendations of a plurality of categories ofrecommendations in which to categorize a point of interest, theplurality of categories of recommendations being based on a regionalprofile of a geographic region, the regional profile including a set ofpoints of interest within the geographic region; means for obtaining,via the user interface of the mobile device, user-uploaded contentassociated with the point of interest; and means for obtaining, via theuser interface of the mobile device, at least one privacy controlassociated with the user-uploaded content.
 47. A non-transitorycomputer-readable medium storing computer-executable instructions, thecomputer-executable instructions comprising: at least one instructioninstructing a mobile device to display a plurality of categories ofrecommendations, the plurality of categories of recommendations beingbased on a regional profile of a geographic region, the regional profileincluding a set of points of interest within the geographic region,wherein the plurality of categories of recommendations is different fora first geographic region of a plurality of geographic regions comparedto a second geographic region of the plurality of geographic regions; atleast one instruction instructing the mobile device to obtain aselection of a category of the plurality of categories ofrecommendations; at least one instruction instructing the mobile deviceto display, responsive to the obtained category of the plurality ofcategories of recommendations, at least one recommended point ofinterest from the set of points of interest via a user interface of themobile device, wherein the at least one recommended point of interest isdisplayed based on at least user ratings of the set of points ofinterest within the geographic region, including the at least onerecommended point of interest; at least one instruction instructing themobile device to obtain a selection of a point of interest from amongthe displayed at least one recommended point of interest; and at leastone instruction instructing the mobile device to display user-uploadedcontent associated with the selected point of interest via the userinterface of the mobile device, the user-uploaded content subject toprivacy controls associated with a set of users that provided theuser-uploaded content.
 48. A non-transitory computer-readable mediumstoring computer-executable instructions, the computer-executableinstructions comprising: at least one instruction instructing anapparatus to obtain, via a user interface of a mobile device, aselection of at least one category of recommendations of a plurality ofcategories of recommendations in which to categorize a point ofinterest, the plurality of categories of recommendations being based ona regional profile of a geographic region, the regional profileincluding a set of points of interest within the geographic region; atleast one instruction instructing the apparatus to obtain, via the userinterface of the mobile device, user-uploaded content associated withthe point of interest; and at least one instruction instructing theapparatus to obtain, via the user interface of the mobile device, atleast one privacy control associated with the user-uploaded content.